{"id":2547,"date":"2022-09-20T19:08:36","date_gmt":"2022-09-20T19:08:36","guid":{"rendered":"https:\/\/salarydistribution.com\/machine-learning\/2022\/09\/20\/keynote-wrap-up-nvidia-ceo-unveils-next-gen-rtx-gpus-ai-workflows-in-the-cloud\/"},"modified":"2022-09-20T19:08:36","modified_gmt":"2022-09-20T19:08:36","slug":"keynote-wrap-up-nvidia-ceo-unveils-next-gen-rtx-gpus-ai-workflows-in-the-cloud","status":"publish","type":"post","link":"https:\/\/salarydistribution.com\/machine-learning\/2022\/09\/20\/keynote-wrap-up-nvidia-ceo-unveils-next-gen-rtx-gpus-ai-workflows-in-the-cloud\/","title":{"rendered":"Keynote Wrap-Up: NVIDIA CEO Unveils Next-Gen RTX GPUs, AI Workflows in the Cloud"},"content":{"rendered":"
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New cloud services<\/a> to support AI workflows and the launch of a new generation of GeForce RTX GPUs<\/a> featured today in NVIDIA CEO Jensen Huang\u2019s GTC keynote, which was packed with new systems, silicon, and software.<\/p>\n

\u201cComputing is advancing at incredible speeds, the engine propelling this rocket is accelerated computing, and its fuel is AI,\u201d Huang said during a virtual presentation as he kicked off NVIDIA GTC<\/a>.<\/p>\n

Again and again, Huang connected new technologies to new products to new opportunities \u2013 from harnessing AI to delight gamers with never-before-seen graphics to building virtual proving grounds where the world\u2019s biggest companies can refine their products.<\/p>\n

Driving the deluge of new ideas, new products and new applications: a singular vision of accelerated computing unlocking advances in AI, which, in turn will touch industries around the world.<\/p>\n

Gamers and creators will get the first GPUs based on the <\/a>new NVIDIA Ada Lovelace architecture<\/a>.<\/p>\n

Enterprises will get powerful new tools for high-performance computing applications with systems based on the Grace CPU and Grace Hopper Superchip<\/a>. Those building the 3D internet will get new OVX servers powered by Ada Lovelace L40 data center GPUs<\/a>. Researchers and computer scientists get new large language model capabilities with NVIDIA LLMs NeMo Service<\/a>. And the auto industry gets Thor, a new brain with an astonishing 2,000 teraflops of performance<\/a>.<\/p>\n

Huang highlighted how NVIDIA\u2019s technologies are being put to work by a sweep of major partners and customers across a breadth of industries.<\/p>\n

To speed adoption, he announced Deloitte, the world\u2019s largest professional services firm, is bringing new services built on NVIDIA AI and NVIDIA Omniverse to the world\u2019s enterprises<\/a>.<\/p>\n

And he shared customer stories from telecoms giant Charter, as well as General Motors in the automotive industry, the German railway system\u2019s Deutsche Bahn<\/a> in transportation, The Broad Institute in medical research<\/a>, and Lowe\u2019s in retail<\/a>.<\/p>\n

NVIDIA GTC, which kicked off this week, has become one of the world\u2019s most important AI gatherings, with 200+ speakers from companies such as Boeing<\/a>, Deutsche Bank<\/a>, Lowe\u2019s<\/a>, Polestar<\/a>, Johnson & Johnson<\/a>, Kroger<\/a>, Mercedes-Benz<\/a>, Siemens AG<\/a>, T-Mobile<\/a>\u00a0and US Bank<\/a>. More than 200,000 people have registered for the conference.<\/p>\n

A \u2018Quantum Leap\u2019: GeForce RTX 40 Series GPUs<\/b><\/h2>\n

First out of the blocks at the keynote was the launch of next-generation GeForce RTX 40 Series GPUs powered by Ada, which Huang called a \u201cquantum leap\u201d that paves the way for creators of fully simulated worlds.<\/p>\n

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NVIDIA CEO Jensen Huang launched the next-generation GeForce RTX 40 Series GPUs.<\/figcaption><\/figure>\n

Huang gave his audience a taste of what that makes possible by offering up a look at Racer RTX, a fully interactive simulation that\u2019s entirely ray traced, with all the action physically modeled.<\/p>\n

Ada\u2019s advancements include a new Streaming Multiprocessor, a new RT Core with twice the ray-triangle intersection throughput, and a new Tensor Core with the Hopper FP8 Transformer Engine and 1.4 petaflops of Tensor processor power.<\/p>\n

Ada also introduces the latest version of NVIDIA DLSS technology<\/a>, DLSS 3, which uses AI to generate new frames by comparing new frames with prior frames to understand how a scene is changing. The result: boosting game performance by up to 4x over brute force rendering.<\/p>\n

DLSS 3 has received support from many of the world\u2019s leading game developers, with more than 35 games and applications announcing support. \u201cDLSS 3 is one of our greatest neural rendering inventions,\u201d Huang said.<\/p>\n

Together, Huang said, these innovations help deliver 4x more processing throughput with the new GeForce RTX 4090 versus its forerunner, the RTX 3090 Ti. \u201cThe new heavyweight champ\u201d starts at $1,599 and will be available Oct. 12.<\/p>\n

Additionally, the new GeForce RTX 4080 is launching in November with two configurations.<\/p>\n

The GeForce RTX 4080 16GB, priced at $1,199, has 9,728 CUDA cores and 16GB of high-speed Micron GDDR6X memory. With DLSS 3, it\u2019s twice as fast in today\u2019s games as the GeForce RTX 3080 Ti,\u00a0 and more powerful than the GeForce RTX 3090 Ti at lower power.<\/p>\n

The GeForce RTX 4080 12GB has 7,680 CUDA cores and 12GB of Micron GDDR6X memory, and with DLSS 3 is faster than the RTX 3090 Ti, the previous-generation flagship GPU. It\u2019s priced at $899.<\/p>\n

Huang also announced that NVIDIA Lightspeed Studios used Omniverse to reimagine Portal<\/i><\/a>, one of the most celebrated games in history. With NVIDIA RTX Remix<\/a>, an AI-assisted toolset, users can mod their favorite games, enabling them to up-res textures and assets, and give materials physically accurate properties.<\/p>\n

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NVIDIA Lightspeed Studios used Omniverse to reimagine Portal, one of the most celebrated games in history.<\/figcaption><\/figure>\n

Powering AI Advances, H100 GPU in Full Production<\/b><\/h2>\n

Once more tying systems and software to broad technology trends, Huang explained that large language models, or LLMs, and recommender systems are the two most important AI models today.<\/p>\n

Recommenders \u201crun the digital economy,\u201d powering everything from e-commerce to entertainment to advertising, he said. \u201cThey\u2019re the engines behind social media, digital advertising, e-commerce and search.\u201d<\/p>\n

And large language models based on the Transformer deep learning model first introduced in 2017 are now among the most vibrant areas for research in AI, and able to learn to understand human language without supervision or labeled datasets.<\/p>\n

\u201cA single pre-trained model can perform multiple tasks, like question answering, document summarization, text generation, translation and even software programming,\u201d Huang said.<\/p>\n

Delivering the computing muscle needed to power these enormous models, Huang said the NVIDIA H100 Tensor Core GPU, with Hopper\u2019s next-generation Transformer Engine, is in full production, with systems shipping in the coming weeks.<\/p>\n

\u201cHopper is in full production and coming soon to power the world\u2019s AI factories,\u201d Huang said.<\/p>\n

Partners building systems include Atos, Cisco, Dell Technologies, Fujitsu, GIGABYTE, Hewlett Packard Enterprise, Lenovo and Supermicro. And Amazon Web Services, Google Cloud, Microsoft Azure and Oracle Cloud Infrastructure will be among the first to deploy H100-based instances in the cloud starting next year.<\/p>\n

And Grace Hopper, which combines NVIDIA\u2019s Arm-based Grace data center CPU with Hopper GPUs, with its 7x increase in fast-memory capacity, will deliver a \u201cgiant leap\u201d for recommender systems, Huang said. Systems incorporating Grace Hopper will be available in the first half of 2023.<\/p>\n

Weaving Together the Metaverse, L40 Data Center GPUs in Full Production<\/b><\/h2>\n

The next evolution of the internet, called the metaverse, will be extended with 3D, Huang explained. Omniverse is NVIDIA\u2019s platform for building and running metaverse applications.<\/p>\n

Here, too, Huang explained how connecting and simulating these worlds will require powerful, flexible new computers. And NVIDIA OVX servers are built for scaling out metaverse applications.<\/p>\n

NVIDIA\u2019s 2nd-generation OVX systems will be powered by Ada Lovelace L40 data center GPUs, which are now in full production, Huang announced.<\/p>\n

Thor for Autonomous Vehicles, Robotics, Medical Instruments and More<\/b><\/h2>\n

In today\u2019s vehicles, active safety, parking, driver monitoring, camera mirrors, cluster and infotainment are driven by different computers. In the future, they\u2019ll be delivered by software that improves over time, running on a centralized computer, Huang said.<\/p>\n

To power this, Huang introduced DRIVE Thor, which combines the transformer engine of Hopper, the GPU of Ada, and the amazing CPU of Grace.<\/p>\n

The new Thor superchip delivers 2,000 teraflops of performance, replacing Atlan on the DRIVE roadmap, and providing a seamless transition from DRIVE Orin, which has 254 TOPS of performance and is currently in production vehicles. Thor will be the processor for robotics, medical instruments, industrial automation and edge AI systems, Huang said.<\/p>\n

3.5 Million Developers, 3,000 Accelerated Applications<\/b><\/h2>\n

Bringing NVIDIA\u2019s systems and silicon, and the benefits of accelerated computing, to industries around the world, is a software ecosystem with more than 3.5 million developers creating some 3,000 accelerated apps using NVIDIA\u2019s 550 software development kits, or SDKs, and AI models, Huang announced.<\/p>\n

And it\u2019s growing fast. Over the past 12 months, NVIDIA has updated more than 100 SDKs and introduced 25 new ones.<\/p>\n

\u201cNew SDKs increase the capability and performance of systems our customers already own, while opening new markets for accelerated computing,\u201d Huang said.<\/p>\n

New Services for AI, Virtual Worlds<\/b><\/h2>\n

Large language models \u201care the most important AI models today,\u201d Huang said. Based on the transformer architecture, these giant models can learn to understand meanings and languages without supervision or labeled datasets, unlocking remarkable new capabilities.<\/p>\n

To make it easier for researchers to apply this \u201cincredible\u201d technology to their work, Huang announced the Nemo LLM Service, an NVIDIA-managed cloud service to adapt pretrained LLMs to perform specific tasks.<\/p>\n

To accelerate the work of drug and bioscience researchers, Huang also announced BioNeMo LLM, a service to create LLMs that understand chemicals, proteins, DNA and RNA sequences.<\/p>\n

Huang announced that NVIDIA is working with The Broad Institute, the world\u2019s largest producer of human genomic information, to make NVIDIA Clara libraries, such as NVIDIA Parabricks, the Genome Analysis Toolkit, and BioNeMo, available on Broad\u2019s Terra Cloud Platform.<\/p>\n

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NVIDIA is working with The Broad Institute, the world\u2019s largest producer of human genomic information, to make NVIDIA Clara libraries available on Broad\u2019s Terra Cloud Platform.<\/figcaption><\/figure>\n

Haung also detailed NVIDIA Omniverse Cloud<\/a>, an infrastructure-as-a-service that connects Omniverse applications running in the cloud, on premises or on a device.<\/p>\n

New Omniverse containers \u2013 Replicator for synthetic data generation, Farm for scaling render farms, and Isaac Sim for building and training AI robots \u2013 are now available for cloud deployment, Huang announced.<\/p>\n

Omniverse is seeing wide adoption, and Huang shared several customer stories and demos:<\/p>\n